{"cells":[{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import numpy as np\n","import pandas as pd\n","from matplotlib import pyplot as plt\n","import torch\n","from torch import nn\n","device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n","# device = 'cpu'"]},{"cell_type":"code","execution_count":2,"metadata":{},"outputs":[],"source":["# 正负样本数量\n","n_positive, n_negative = 2000, 2000\n","\n","# 生成正样本, 小圆环分布\n","r_p = 5.0 + torch.normal(0.0, 1.0, size=[n_positive, 1])\n","theta_p = 2 * np.pi * torch.rand([n_positive, 1])\n","Xp = torch.cat([r_p * torch.cos(theta_p), r_p * torch.sin(theta_p)], axis=1)\n","Yp = torch.ones_like(r_p)\n","\n","# 生成负样本, 大圆环分布\n","r_n = 8.0 + torch.normal(0.0, 1.0, size=[n_negative, 1])\n","theta_n = 2 * np.pi * torch.rand([n_negative, 1])\n","Xn = torch.cat([r_n * torch.cos(theta_n), r_n * torch.sin(theta_n)], axis=1)\n","Yn = torch.zeros_like(r_n)\n","\n","# 汇总样本\n","X = torch.cat([Xp, Xn], axis=0)\n","Y = torch.cat([Yp, Yn], axis=0)\n"]},{"cell_type":"code","execution_count":3,"metadata":{},"outputs":[{"data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{},"output_type":"display_data"},{"data":{"image/png":"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","text/plain":["<Figure size 432x432 with 1 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["# 可视化\n","plt.clf()\n","plt.figure(figsize=(6, 6))\n","plt.scatter(Xp[:, 0].numpy(), Xp[:, 1].numpy(), c=\"r\")\n","plt.scatter(Xn[:, 0].numpy(), Xn[:, 1].numpy(), c=\"g\")\n","plt.legend([\"positive\", \"negative\"])\n","# plt.savefig(\"./dnn_test_raw.png\")\n","plt.show()"]},{"cell_type":"code","execution_count":4,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["tensor([[-4.6522,  1.2448],\n","        [-0.4231, -5.4234],\n","        [ 0.6889, -4.1967],\n","        [-2.1229,  6.9828],\n","        [ 1.1719,  8.1696],\n","        [ 6.3048,  3.8412],\n","        [ 6.5394,  1.1554],\n","        [ 4.1297, -2.8531]])\n","tensor([[1.],\n","        [1.],\n","        [1.],\n","        [0.],\n","        [0.],\n","        [0.],\n","        [1.],\n","        [1.]])\n"]}],"source":["# 构建数据管道迭代器\n","def data_iter(features, labels, batch_size=8):\n","    num_examples = len(features)\n","    indices = list(range(num_examples))\n","    np.random.shuffle(indices)  # 样本的读取顺序是随机的\n","    for i in range(0, num_examples, batch_size):\n","        indexs = torch.LongTensor(indices[i: min(i + batch_size, num_examples)])\n","        yield features.index_select(0, indexs), labels.index_select(0, indexs)\n","\n","\n","# 测试数据管道效果\n","batch_size = 8\n","(features, labels) = next(data_iter(X, Y, batch_size))\n","print(features)\n","print(labels)"]},{"cell_type":"code","execution_count":5,"metadata":{},"outputs":[],"source":["class DNNModel(nn.Module):\n","    def __init__(self):\n","        super(DNNModel, self).__init__()\n","        self.w1 = nn.Parameter(torch.randn(2, 4))\n","        self.b1 = nn.Parameter(torch.zeros(1, 4))\n","        self.w2 = nn.Parameter(torch.randn(4, 8))\n","        self.b2 = nn.Parameter(torch.zeros(1, 8))\n","        self.w3 = nn.Parameter(torch.randn(8, 1))\n","        self.b3 = nn.Parameter(torch.zeros(1, 1))\n","\n","    # 正向传播\n","    def forward(self, x):\n","        x = torch.relu(x @ self.w1 + self.b1)\n","        x = torch.relu(x @ self.w2 + self.b2)\n","        y = torch.sigmoid(x @ self.w3 + self.b3)\n","        return y\n","\n","    # 损失函数(二元交叉熵)\n","    def loss_func(self, y_pred, y_true):\n","        # 将预测值限制在1e-7以上, 1- (1e-7)以下，避免log(0)错误\n","        eps = 1e-7\n","        y_pred = torch.clamp(y_pred, eps, 1.0 - eps)\n","        bce = - y_true * torch.log(y_pred) - (1 - y_true) * torch.log(1 - y_pred)\n","        return torch.mean(bce)\n","\n","    # 评估指标(准确率)\n","    def metric_func(self, y_pred, y_true):\n","        y_pred = torch.where(y_pred > 0.5, torch.ones_like(y_pred, dtype=torch.float32),\n","                             torch.zeros_like(y_pred, dtype=torch.float32))\n","        acc = torch.mean(1 - torch.abs(y_true - y_pred))\n","        return acc\n","        \n","model = DNNModel()"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["init loss: 5.732353210449219\n","init metric: 0.6430714726448059\n"]}],"source":["# 测试模型结构\n","batch_size = 10\n","(features, labels) = next(data_iter(X, Y, batch_size))\n","\n","predictions = model(features)\n","\n","loss = model.loss_func(labels, predictions)\n","metric = model.metric_func(labels, predictions)\n","\n","print(\"init loss:\", loss.item())\n","print(\"init metric:\", metric.item())"]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["\n","================================================================================2022-03-13 21:37:16\n","epoch = 100 loss =  0.19827325079590083 metric =  0.9242500084638595\n","\n","================================================================================2022-03-13 21:38:30\n","epoch = 200 loss =  0.19069937812164425 metric =  0.9240000107884407\n","\n","================================================================================2022-03-13 21:39:35\n","epoch = 300 loss =  0.18051471719983966 metric =  0.9282500091195106\n","\n","================================================================================2022-03-13 21:40:41\n","epoch = 400 loss =  0.1763887820811942 metric =  0.9295000091195107\n","\n","================================================================================2022-03-13 21:41:47\n","epoch = 500 loss =  0.17394351542228834 metric =  0.9350000068545341\n"]}],"source":["# 打印时间\n","import datetime\n","\n","\n","def print_bar():\n","    nowtime = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')\n","    print(\"\\n\" + \"==========\" * 8 + \"%s\" % nowtime)\n","\n","\n","def train_step(model, features, labels):\n","    # 正向传播求损失\n","    features = features.to(device)\n","    labels = labels.to(device)\n","    model = model.to(device)\n","    predictions = model.forward(features)\n","    loss = model.loss_func(predictions, labels)\n","    metric = model.metric_func(predictions, labels)\n","\n","    # 反向传播求梯度\n","    loss.backward()\n","\n","    # 梯度下降法更新参数\n","    for param in model.parameters():\n","        # 注意是对param.data进行重新赋值,避免此处操作引起梯度记录\n","        # param.data = (param.data - 0.01 * param.grad.data)\n","        with torch.no_grad():\n","            param -= 0.01 * param.grad\n","\n","        # 梯度清零\n","    model.zero_grad()\n","    return loss.item(), metric.item()\n","\n","\n","def train_model(model, epochs):\n","    for epoch in range(1, epochs + 1):\n","        loss_list, metric_list = [], []\n","        for features, labels in data_iter(X, Y, 20):\n","            features.to(device)\n","            labels.to(device)\n","            lossi, metrici = train_step(model, features, labels)\n","            loss_list.append(lossi)\n","            metric_list.append(metrici)\n","        loss = np.mean(loss_list)\n","        metric = np.mean(metric_list)\n","\n","        if epoch % 100 == 0:\n","            print_bar()\n","            print(\"epoch =\", epoch, \"loss = \", loss, \"metric = \", metric)\n","\n","model = model.to(device)\n","train_model(model, epochs=500)"]},{"cell_type":"code","execution_count":10,"metadata":{},"outputs":[{"data":{"text/plain":["<Figure size 432x288 with 0 Axes>"]},"metadata":{},"output_type":"display_data"},{"data":{"image/png":"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","text/plain":["<Figure size 864x360 with 2 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["# 结果可视化\n","plt.clf()\n","fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(12, 5))\n","ax1.scatter(Xp[:, 0], Xp[:, 1], c=\"r\")\n","ax1.scatter(Xn[:, 0], Xn[:, 1], c=\"g\")\n","ax1.legend([\"positive\", \"negative\"])\n","ax1.set_title(\"y_true\")\n","\n","Xp_pred = X[torch.squeeze(model.forward(X) >= 0.5)]\n","Xn_pred = X[torch.squeeze(model.forward(X) < 0.5)]\n","\n","ax2.scatter(Xp_pred[:, 0], Xp_pred[:, 1], c=\"r\")\n","ax2.scatter(Xn_pred[:, 0], Xn_pred[:, 1], c=\"g\")\n","ax2.legend([\"positive\", \"negative\"])\n","ax2.set_title(\"y_pred\")\n","plt.show()\n"]}],"metadata":{"interpreter":{"hash":"91479e0ac678ca657dc43e76085b9546b76f7aea8f2d6a14d266a829f6036d13"},"kernelspec":{"display_name":"Python 3.8.12 ('deep-tools')","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.8.12"},"orig_nbformat":4},"nbformat":4,"nbformat_minor":2}
